Publications by authors named "Amalia Plotogea"
Article Synopsis
- The FDA's Center for Biologics Evaluation and Research monitors the safety and effectiveness of biologic products, including vaccines, but often misses key data in electronic health records (EHRs) due to it being found primarily in clinical notes.
- A natural language processing (NLP) algorithm was developed to identify vaccine administrations documented in clinical notes that are not captured in structured EHR data, improving the monitoring of vaccine safety.
- In a study, the NLP algorithm successfully identified an additional 1,183 vaccine administrations from clinical notes, indicating a 16.8% increase in total identified vaccine events compared to relying solely on structured data.
Introduction: Although prognostic differences between screen-detected, interval and symptomatic breast cancers are known, factors associated with wait times to diagnosis among these three groups have not been studied.
Methods: Of the 16,373 invasive breast cancers diagnosed between January 1, 1995 and December 31, 2003 in a cohort of Ontario women aged 50 to 69, a random sample (N = 2,615) were selected for chart abstraction. Eligible women were classified according to detection method; screen-detected (n = 1181), interval (n = 319) or symptomatic (n = 406).
Background: Longer times from diagnosis to breast cancer treatment are associated with poorer prognosis. This study examined factors associated with wait times by phase in the breast cancer treatment pathway.
Methods: There were 1760 women eligible for the study, aged 50-69 diagnosed in Ontario with invasive breast cancer from 1995-2003.